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What can primary care prescribing data tell us about individual adherence to long‐term medication?—comparison to pharmacy dispensing data
Author(s) -
Mabotuwana Thusitha,
Warren Jim,
Harrison Jeff,
Kenealy Timothy
Publication year - 2009
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.1803
Subject(s) - medicine , medical prescription , pharmacy , medical record , reimbursement , pharmacoepidemiology , electronic prescribing , emergency medicine , family medicine , pediatrics , health care , pharmacology , economics , economic growth
Purpose To assess the predictive value of general practice electronic prescribing records with respect to adherence to long‐term medications as compared to claims‐based pharmacy dispensing data. Methods A total of 29772 electronic prescribing records relating to 2713 patients attending a New Zealand general medical practice were linked by national health identifier to 63 833 dispensing records used for community pharmacy reimbursement. Individual possession ratios—prescription possession ratio (PPR) for prescribing and medication possession ratio (MPR) for dispensing—were calculated for the 15‐month period from 1 January 2006 to 30 March 2007 based on each data source for the common long‐term medications simvastatin, metoprolol succinate, bendrofluazide, felodipine, cilazapril and metformin. Results Out of 646 patients prescribed at least one of the six medications by the practice during the 15‐month period, 50% of patients maintained high adherence (MPR ≥ 80%) to all (out of the 6) medications that they were prescribed over the period, with rates of high adherence to individual medications ranging from 68 (felodopine) to 55% (metformin). In 93% of 4043 cases where there was a prescription in the general practice data, a subsequent dispensing record for the same patient and drug was present with a time‐stamp no more than seven days later. PPR < 80% demonstrated a positive predictive value (PPV) of 81.4% (95%CI 78–85%) and negative predictive value (NPV) of 76.3% (95%CI 73–79%) for MPR < 80%. Conclusion There is potential for general practices to identify substantial levels of long‐term medication adherence problems through their electronic prescribing records. Significant further adherence problems could be detected if an e‐pharmacy network allowed practices to match dispensing against prescriptions. Copyright © 2009 John Wiley & Sons, Ltd.

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